There are several classes of post hoc explanation methods, including salience maps,
local surrogate models,
and global interpretation techniques.
A comprehensive overview can be found in [1]}, [2]}.
However, here we strictly focus on model agnostic local approximation, which is one of the most prevalent explanation strategies.
Specifically, we will consider the LIME [3]}, SHAP [4]}, and MAPLE [5]} explainers.
Previously, LIME has been shown to produce unstable explanations for similar inputs [6]}, [7]}, and an analysis indicated that it can produce inaccurate explanations [8]}.
In an adversarial context, LIME and SHAP have been shown to be deceivable by employing an out-of-distribution detector to mask prejudiced decisions [9]}.
